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Kristi answered on March 29, 2020 Popularity 10/10 Helpfulness 4/10

answer get_dummies

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get_dummies

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#this do dummie verable do a very intersting thing they turn calegorical 
#variables in numerical like M and F they can 0 for M and 1 for F  


pd.get_dummies(df.Gender)

	F	M
0	0	1
1	1	0
2	1	0
3	0	1
4	1	0
...	...	...
202	1	0
203	0	1
204	0	1
205	0	1
206	1	0
207 rows × 2 columns

Popularity 10/10 Helpfulness 4/10 Language python

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Tags: python

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Contributed on Sep 22 2021

Kristi

0 Answers Avg Quality 2/10

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# Binary Encoding
df["cat_col"] = df["cat_col"].apply(lambda val: 1 if val == "y" else 0)

# One-hot-encoding on categorical variable
df_onehot = pd.get_dummies(df, columns=['cat'], prefix='C')
df_dummy = pd.get_dummies(df, columns=['cat'], drop_first=True, prefix='C')

# Alternative approach-2
from sklearn import preprocessing
encoder = preprocessing.OneHotEncoder()
onehot_transformed = encoder.fit_transform(df['cat_col'].values.reshape(-1,1))
# Convert into dataframe
onehot_df = pd.DataFrame(onehot_transformed.toarray())
# Add the encoded columns with original dataset, 
df = pd.concat([df, onehot_df], axis=1)
# Drop the original column that you used for encoding 
df = df.drop('cat_col', axis=1)

# Label encoding : Turning string labels into numeric values
from sklearn import preprocessing
encoder_lvl = preprocessing.LabelEncoder()
# Specify the unique categories in the column to apply one-hot encoding
encoder_lvl.fit([ 'LOW', 'NORMAL', 'HIGH'])
# Apply one hot encoding on the third column of the dataset
df[:,2] = encoder_lvl.transform(df[:,2]) 

# Alternative approach : DictVectorizer
from sklearn.feature_extraction import DictVectorizer

df_dict = df.to_dict("records") # Convert df into a list of dictionary
dv = DictVectorizer(sparse = False)
df_encoded = dv.fit_transform(df_dict)
print(df_encoded[:5,:]) # Print first five rows
# Print the vocabulary (how the features are mapped to columns in the resulting matrix.)
print(dv.vocabulary_)

# Alternative appraach : Use pandas only
# Turn response variable into labeled codes
df.cat_col = pd.Categorical(df.cat_col)
df.cat_col = df.cat_col.cat.codes

Popularity 9/10 Helpfulness 4/10 Language python

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Tags: python py

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Contributed on Jan 11 2024

Innocent Iguana

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pd.get_dummies

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>>> s = pd.Series(list('abca'))

>>> pd.get_dummies(s)
   a  b  c
0  1  0  0
1  0  1  0
2  0  0  1
3  1  0  0

Popularity 10/10 Helpfulness 4/10 Language python

Source: pandas.pydata.org

Tags: python py

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Contributed on Mar 29 2020

Gifted Gecko

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get_dummies

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